Acoustic emission (AE) technique has recently been extensively used in machine health monitoring and\ndiagnosis of diesel engine. Although it offers many advantages for early detection of fault symptoms, it also comes\nwith many challenging problems. Due to its operation in high frequency range (stress waves), from a few kHz to MHz,\nit poses a problem of massive data storage and transmission. Furthermore, the non-linearity of AE sensors is also\nanother challenge as it does not provide any quantitative/comparative analysis if multiple sensors are used, such\nin multi-cylinder diesel engine. Hence, this short paper will present the work carried out in the author�s laboratory\nby introducing a simple and innovative data reduction process termed as Peak Hold down Sampling (PHDS) and a\nnormalization approach for diagnosis of diesel engine.
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